University of Twente Student Theses
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Predicting complications and grading the difficulty of total mesorectal excision surgery using machine learning
Barendsen, BSc Sander N. (2025) Predicting complications and grading the difficulty of total mesorectal excision surgery using machine learning.
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| Abstract: | In this thesis, machine learning and deep learning are used to develop a model that predicts the probability of anastomotic leakage and Clavien-Dindo grade 3+ complications in patients undergoing total mesorectal excision surgery. Additionally, a proof-of-concept dashboard is developed using Flask and Dash to assist surgeons in the outpatient clinic. |
| Item Type: | Essay (Master) |
| Faculty: | TNW: Science and Technology |
| Subject: | 30 exact sciences in general, 44 medicine, 50 technical science in general, 54 computer science |
| Programme: | Technical Medicine MSc (60033) |
| Link to this item: | https://purl.utwente.nl/essays/104909 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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